Stream-based data deduplication using directed cyclic graphs to facilitate on-the-wire compression

ABSTRACT

Stream-based data deduplication is provided in a multi-tenant shared infrastructure but without requiring “paired” endpoints having synchronized data dictionaries. Data objects processed by the dedupe functionality are treated as objects that can be fetched as needed. As such, a decoding peer does not need to maintain a symmetric library for the origin. Rather, if the peer does not have the chunks in cache that it needs, it follows a conventional content delivery network procedure to retrieve them. In this way, if dictionaries between pairs of sending and receiving peers are out-of-sync, relevant sections are then re-synchronized on-demand. The approach does not require that libraries maintained at a particular pair of sender and receiving peers are the same. Rather, the technique enables a peer, in effect, to “backfill” its dictionary on-the-fly. On-the-wire compression techniques are provided to reduce the amount of data transmitted between the peers.

BACKGROUND Technical Field

This application relates generally to data communication over a network.

Brief Description of the Related Art

Distributed computer systems are well-known in the prior art. One suchdistributed computer system is a “content delivery network” or “CDN”that typically is operated and managed by a service provider. Theservice provider typically provides the content delivery service onbehalf of third parties (customers) who use the service provider'sshared infrastructure. A distributed system of this type is sometimesreferred to as an “overlay network” and typically refers to a collectionof autonomous computers linked by a network or networks, together withthe software, systems, protocols and techniques designed to facilitatevarious services, such as content delivery, application acceleration, orother support of outsourced origin site infrastructure. A CDN serviceprovider typically provides service delivery through digital properties(such as a website), which are provisioned in a customer portal and thendeployed to the network.

Data differencing is a known technology and method to leverage sharedprior instances of a resource, also known as versions of data within ashared dictionary in compression terminology, between a server and aclient; the process works by only sending the differences or changesthat have occurred since those prior instance(s). Data differencing isrelated to compression, but it is a slightly distinct concept. Inparticular, intuitively, a difference (“diff”) is a form of compression.As long as the receiver has the same original file as a sender, thatsender can give the receiver a diff instead of the entire new file. Thediff in effect explains how to create the new file from the old. It isusually much smaller than the whole new file and thus is a form ofcompression. The diff between a first version of a document and a secondversion of that same document is the data difference; the datadifference is the result of compression of the second version of adocument using the first version of the document as a preset dictionary.

Stream-based data deduplication (“dedupe”) systems are also known in theprior art. In general, stream-based data deduplication systems work byexamining the data that flows through a sending peer of a connection andreplacing blocks of that data with references that point into a shareddictionary that each peer has synchronized around the given blocks. Thereference itself is much smaller than the data and often is a hash orfingerprint of it. When a receiving peer receives the modified stream,it replaces the reference with the original data to make the streamwhole again. For example, consider a system where the fingerprint is aunique hash that is represented with a single letter variable. Thesending peer's dictionary then might look as shown in FIG. 3. Thereceiving peer's dictionary might look as shown in FIG. 4. Then, forexample, if the sending peer is supposed to send a string such as“Hello, how are you? Akamai is Awesome!” the deduplication system wouldinstead process the data and send the following message: “He[X]re you?[T][M] ome!” The receiving peer decodes the message using itsdictionary. Note that, in this example, the sending peer does notreplace “ome!” with the reference [O]. This is because, although thesending peer has a fingerprint and block stored it its cache, that peerknows (through a mechanism) that the receiving peer does not. Therefore,the sending peer does not insert the reference in the message beforesending it. A system of this type typically populates the dictionaries,which are symmetric, in one of several, known manners. In one approach,dictionary data is populated in fixed length blocks (e.g., every blockis 15 characters in length) as a stream of data flows through the dataprocessor. The first time the data passes through both the sending andreceiving peers, and assuming they both construct dictionaries in thesame way, both peers end up having a dictionary that contains the sameentries. This approach, however, is non-optimal, as it is subject to aproblem known as the “shift” problem, which can adversely affect thegenerated fingerprints and undermining the entire scheme.

An alternative approach uses variable-length blocks using hashescomputed in a rolling manner. In a well-known solution based on atechnique known as Rabin fingerprinting, the system slides a window of acertain size (e.g., 48 bytes) across a stream of data during thefingerprinting process. An implementation of the technique is describedin a paper titled “A Low-Bandwidth Network File System” (LBFS), byMuthitacharoen et al, and the result achieves variable sizeshift-resistant blocks.

Current vendors supplying stream-based data deduplication products andservices address the problem of dictionary discovery (knowing whatinformation is in a peer's dictionary) by pairing devices. Thus, forexample, appliance/box vendors rely on a pair of devices or processes oneach end to communicate with each other to maintain tables that let eachside know what references exist in the paired peer. This type ofsolution, however, only works when dealing with individual boxes andunits that represent “in path” pairs.

In path-paired solutions, however, are not practical in the context ofan overlay network such as a CDN, where the distribution of nodes moreclosely resembles a tree. Thus, for example, in a representativeimplementation, and with respect to a particular origin server (or, moregenerally, a “tenant” located at a “root”), the overlay may have parenttier servers closer to the root, and client edge servers closer to theleaf nodes. In other words, instead of a box needing to be aware of asmall set of one or more peer boxes (such as in known box vendorsolutions), a parent tier server may need to be in contact with tens,hundreds or even thousands of edge regions, each containing potentiallymany servers. In this context, per machine tables cannot scale.

Thus, there remains a need to provide enhanced techniques for datadeduplication in the context of an overlay network.

BRIEF SUMMARY

An Internet infrastructure delivery platform (e.g., operated by aservice provider) provides an overlay network (a “multi-tenant sharedinfrastructure”). A particular tenant has an associated origin. One ormore overlay network servers that are near a tenant origin are equippedwith a dedupe engine that provides data deduplication. These servers arededupe cache parents for that origin in that they receive requests fromoverlay network cache childs, typically edge servers that are locatednear to end user access networks. An edge server also includes a dedupeengine. When a request for origin content arrives from an overlaynetwork edge server, the request is routed through a dedupe cache parentfor the origin. The cache parent retrieves the content (perhaps from theorigin) and then performs a traditional dedupe operation. In particular,the cache parent first looks into its “library” (or “dictionary”) forthe origin and sees if it can compress the object by replacing chunks ofbytes that it has already seen with the names that have already beenassigned for those chunks. This operation “compresses” the object in aknown manner. The cache parent then sends the compressed object to theoverlay network edge server, where it is processed by the edge serverdedupe engine. Outside of this delivery loop, however, the dedupe cacheparent also processes the object to store newly-seen chunks of bytes,and entering the new chunks into the library (or “dictionary”) that itmaintains. When the compressed stream is received at the overlay networkedge server, the edge server processes the compressed stream by lookingfor chunks that were replaced by names (or “fingerprints”), and thenretrieving the original chunks using the fingerprints as keys into itsown dictionary.

If the edge server does not have the chunks in cache that it needs, itfollows a conventional CDN approach to retrieve them (e.g., through acache hierarchy or the like), ultimately retrieving them from the dedupecache parent if necessary. Thus, if dictionaries between pairs ofsending and receiving peers are out-of-sync, relevant sections are thenre-synchronized on-demand. The approach does not require (or require aguarantee) that libraries maintained at a particular pair of sender andreceiving peers are the same (i.e., synchronized). Rather, the techniqueenables a peer, in effect, to “backfill” its dictionary on-the-fly inassociation with an actual transaction. This approach is highlyscalable, and it works for any type of content, and over any type ofnetwork.

Additional on-the-wire compression between a pair of deduplicationengines is provided by maintaining a unique form of data structure oneach side of the connection. Preferably, the data structure is a“directed cyclic graph” (DCG), wherein a given DCG represents temporaland ordered relationships between (and among) chunks of data that havebeen seen in a data stream by the peer. In particular, a DCG comprisesone or more nodes, each of which represent a chunk of data, a label thatrepresents or is the fingerprint, and an edge (e.g., an arrow) thatrepresents a transition that the peer has seen in the data stream withrespect to that chunk. A node has a set of allowed state transitions.For example, a node that has one just one (1) “out” (an arrow that leadsaway from the node) is an Intermediate Node, and a stretch of nodes eachwith degree 1 “out” and that are connected together are referred to as aStrand. A Strand Record defines the particular nodes (and theirfingerprints) that comprise a Strand. When the content that traversesthe peers has large strings of data (e.g., in file headers) that doesnot change, it is likely that there will be a large number of nodes inthe resulting DCGs that include Strands. Thus, the transmission ofStrand Records between cooperating dedupe engines can significantlyreduce the amount of information transmitted on the wire during thededuplication process. In particular, once the DCG is in place on bothpeers, an encoding scheme is then carried out using the Strand Recordswhere appropriate (i.e., where the DCG includes Strands) such that theamount of data that is placed on the wire is substantially reduced (bysending the Strand Record in lieu of the actual node and fingerprintdata making up the Strand). Then, when there is a mismatch between thecaches, a decoding peer can make a request (a Missing Strand Request)back up to an encoding peer and request the raw data represented by thenoted strand.

The foregoing has outlined some of the more pertinent features of thesubject matter. These features should be construed to be merelyillustrative. Many other beneficial results can be attained by applyingthe disclosed subject matter in a different manner or by modifying thesubject matter as will be described.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the subject matter and theadvantages thereof, reference is now made to the following descriptionstaken in conjunction with the accompanying drawings, in which:

FIG. 1 is a block diagram illustrating a known distributed computersystem configured as a content delivery network (CDN);

FIG. 2 is a representative CDN edge machine configuration;

FIG. 3 is a sending peer dictionary in a data differencing process;

FIG. 4 is a receiving peer dictionary in a data differencing process;

FIG. 5 is an exemplary wide area network (WAN) architecture forimplementing an asynchronous data dictionary approach;

FIG. 6 is a specific embodiment of the technique shown in FIG. 5implemented within an overlay network and a customer private network;

FIG. 7 illustrates a representative directed cyclic graph (DCG) of a setof chunks of data that have been seen by a peer in the deduplicationscheme described;

FIG. 8 illustrates a modification of the DCG in FIG. 7 following receiptof another stream of data at the peer; and

FIG. 9 illustrates a modification of the DCG in FIG. 8 to illustrate howa portion of the stream may loop back on itself.

DETAILED DESCRIPTION

FIG. 1 illustrates a known distributed computer system that (asdescribed below) is extended by the techniques herein.

In a known system, such as shown in FIG. 1, a distributed computersystem 100 is configured as a CDN and is assumed to have a set ofmachines 102 a-n distributed around the Internet. Typically, most of themachines are servers located near the edge of the Internet, i.e., at oradjacent end user access networks. A network operations command center(NOCC) 104 manages operations of the various machines in the system.Third party sites, such as web site 106, offload delivery of content(e.g., HTML, embedded page objects, streaming media, software downloads,and the like) to the distributed computer system 100 and, in particular,to “edge” servers. Typically, content providers offload their contentdelivery by aliasing (e.g., by a DNS CNAME) given content providerdomains or sub-domains to domains that are managed by the serviceprovider's authoritative domain name service. End users that desire thecontent are directed to the distributed computer system to obtain thatcontent more reliably and efficiently. Although not shown in detail, thedistributed computer system may also include other infrastructure, suchas a distributed data collection system 108 that collects usage andother data from the edge servers, aggregates that data across a regionor set of regions, and passes that data to other back-end systems 110,112, 114 and 116 to facilitate monitoring, logging, alerts, billing,management and other operational and administrative functions.Distributed network agents 118 monitor the network as well as the serverloads and provide network, traffic and load data to a DNS query handlingmechanism 115, which is authoritative for content domains being managedby the CDN. A distributed data transport mechanism 120 may be used todistribute control information (e.g., metadata to manage content, tofacilitate load balancing, and the like) to the edge servers.

As illustrated in FIG. 2, a given machine 200 comprises commodityhardware (e.g., an Intel Pentium processor) 202 running an operatingsystem kernel (such as Linux or variant) 204 that supports one or moreapplications 206 (FIG. 2, element 206). To facilitate content deliveryservices, for example, given machines typically run a set ofapplications, such as an HTTP (web) proxy 207, a name server 208, alocal monitoring process 210, a distributed data collection process 212,and the like. For streaming media, the machine typically includes one ormore media servers, such as a Windows Media Server (WMS) or Flashserver, as required by the supported media formats.

A CDN edge server is configured to provide one or more extended contentdelivery features, preferably on a domain-specific, customer-specificbasis, preferably using configuration files that are distributed to theedge servers using a configuration system. A given configuration filepreferably is XML-based and includes a set of content handling rules anddirectives that facilitate one or more advanced content handlingfeatures. The configuration file may be delivered to the CDN edge servervia the data transport mechanism. U.S. Pat. No. 7,111,057 illustrates auseful infrastructure for delivering and managing edge server contentcontrol information, and this and other edge server control informationcan be provisioned by the CDN service provider itself, or (via anextranet or the like) the content provider customer who operates theorigin server.

Because the CDN infrastructure is shared by multiple third parties, itis sometimes referred to herein as a multi-tenant shared infrastructure.The CDN processes may be located at nodes that are publicly-routable onthe Internet, within or adjacent nodes that are located in mobilenetworks, in or adjacent enterprise-based private networks, or in anycombination thereof.

An overlay network web proxy (such as proxy 207 in FIG. 2) that ismetadata-configurable is sometimes referred to herein as a global hostor GHost process.

The CDN may include a storage subsystem, such as described in U.S. Pat.No. 7,472,178, the disclosure of which is incorporated herein byreference.

The CDN may operate a server cache hierarchy to provide intermediatecaching of customer content; one such cache hierarchy subsystem isdescribed in U.S. Pat. No. 7,376,716, the disclosure of which isincorporated herein by reference.

The CDN may provide secure content delivery among a client browser, edgeserver and customer origin server in the manner described in U.S.Publication No. 20040093419. Secure content delivery as describedtherein enforces SSL-based links between the client and the edge serverprocess, on the one hand, and between the edge server process and anorigin server process, on the other hand. This enables an SSL-protectedweb page and/or components thereof to be delivered via the edge server.

As an overlay, the CDN resources may be used to facilitate wide areanetwork (WAN) acceleration services between enterprise data centers(which may be privately-managed) and third party software-as-a-service(SaaS) providers.

In a typical operation, a content provider identifies a content providerdomain or sub-domain that it desires to have served by the CDN. The CDNservice provider associates (e.g., via a canonical name, or CNAME) thecontent provider domain with an edge network (CDN) hostname, and the CDNprovider then provides that edge network hostname to the contentprovider. When a DNS query to the content provider domain or sub-domainis received at the content provider's domain name servers, those serversrespond by returning the edge network hostname. The edge networkhostname points to the CDN, and that edge network hostname is thenresolved through the CDN name service. To that end, the CDN name servicereturns one or more IP addresses. The requesting client browser thenmakes a content request (e.g., via HTTP or HTTPS) to an edge serverassociated with the IP address. The request includes a host header thatincludes the original content provider domain or sub-domain. Uponreceipt of the request with the host header, the edge server checks itsconfiguration file to determine whether the content domain or sub-domainrequested is actually being handled by the CDN. If so, the edge serverapplies its content handling rules and directives for that domain orsub-domain as specified in the configuration. These content handlingrules and directives may be located within an XML-based “metadata”configuration file.

As additional background, the techniques described in U.S. Pat. Nos.6,820,133 and 7,660,296 may be used to facilitate packet deliverybetween edge and forward proxies in an overlay network such as shown inFIG. 1.

Stream-Based Data Deduplication Using Asynchronous Data Dictionaries

With the above as background, the approach of this disclosure is nowdescribed. In contrast to known stream-based data deduplication productsand services that address the problem of dictionary discovery (knowingwhat information in in a peer's dictionary) by pairing, the techniquesherein operate according to a different paradigm.

In particular, and for certain sized objects, a peer node is “assumed”to have a block associated with a fingerprint, whether or not itactually does. In this approach, the technique does not require (orrequire a guarantee) that libraries maintained at either end (of anyparticular pair of sender and receiving peers) are the same. Rather, inthis approach, a library is created, and that library is the allowed tobe accessible (e.g., over the web). The library can be located anywhere.As will be seen, this approach enables the standard CDN functions andfeatures to be leveraged, thus providing end users (including those onboth fixed line and non-fixed-line networks, and irrespective ofapplication type) both the benefits of deduplication as well as thoseafforded by overlay networking technologies. In this alternativeapproach, if the peer does not have the block associated with a givenfingerprint, the peer makes a request back to the sending agent torequest it. In one embodiment, each block has a particular URIassociated therewith, such as a magnet-style URI. A magnet URI refers toa resource available for download via a description of its content in areduced form (e.g., a cryptographic hash value of the content). Analternative to using a magnet URI is to have a decoding (receiving orchild) peer make a request back up to the encoding (sending or parent)peer (or peer region) and request the raw data for whatever chunk is notthen available to the decoding peer for decode—using some agreed-uponprotocol. Preferably, the processing of data on the decoder side is veryfast, and thus a missing chunk is detected and a request sent back tothe encoder within some small processing overhead time.

Preferably, special care is taken to avoid extraneous round trips backto the sending peer for blocks that are missing. Therefore, in oneembodiment, files that are very small and capable of being sent in oneinitial congestion window (CWND) are not deduplicated, as the risk of ablock cache miss is greater than the payout when the block exists at thereceiving peer. This is because the serialization delay into a networkI/O card is significantly smaller than the latency that might occur on acache miss. Thus, preferably only those responses where there is astatistical probability of any advantage using deduplication (even inthe face of possible extra latency due to missing blocks) should beconsidered.

Thus, according to this disclosure, the deduplication system uses anon-demand cache synchronization protocol, which may involve peerscommunicating with each other explicitly, and that involves a peermaking certain assumptions about what another peer might have, orotherwise. According to this protocol, there is an assumption that thedecoding peer has a given block of data if the local encoding peeralready has it, and an assumption that the decoding peer entity does nothave the given block of data if the local encoding peer does not.Further, the system accounts for a mismatch in caches between peers. Ifthis occurs, the mismatch is resolved. To this end, whenever some data(an object, a chunk, a set of chunks, etc. that have been seen in astream) is not available for decode, the decoding peer makes a requestback up to the encoding peer (or region of peers) and requests the rawdata needed. As noted above, the processing of data on the decoder sideis very fast and thus the missing data is detected and a request sentback to the encoder within only a small processing overhead time. Thisapproach ensures that, irrespective of what cache synchronizationprotocol is being utilized, there is a fallback mechanism to ensure thata transaction can complete. The missing data support thus handles thepossibility of complete cache misses, and it can be used in conjunctionwith the cache synchronization approach described above.

A representative architecture for implementing a deduplication approachof this type is shown in FIG. 5. For simplicity, a client 500 is showninteracting with an edge GHost process 502, which in turn communicates(typically over a WAN) with a forward GHost process 504 located near atenant origin 506. Each GHost process 502 and 504 has associatedtherewith a deduplication engine 508, an associated data store for thedictionary, and other related processes. Collectively, these elementsare sometimes referred to as a dedupe module. The cache parent may alsoimplement other technologies, such as front end optimization (FEO).GHost communicates with the deduplication module over some interface. Inan alternative embodiment, the deduplication functionality isimplemented in GHost natively. When a request for origin content arrivesfrom process 502, the request is routed through the cache parent 504 forthe origin. The cache parent 504 retrieves the content (perhaps from theorigin) and then performs a traditional dedupe operation, using itsdedupe engine 508. In particular, the cache parent first looks into itslibrary and sees if it can compress the object by replacing chunks ofbytes that it has already seen with the names that have already beenassigned for those chunks. Preferably, a library is shared amongmultiple CDN customers; in an alternative embodiment, a library isspecific to a particular origin. The cache parent 504 then sends thecompressed object to edge server process 502, where it is processed bythe edge server dedupe engine 508. Outside of this delivery loop,however, the dedupe cache parent 504 also processes the object to storenewly-seen chunks of bytes, entering the new chunks into its library.When the compressed stream is received at the edge server process 502,the edge server processes the compressed object by looking for chunksthat were replaced by names (or “fingerprints”), and then retrieving theoriginal chunks using the name.

A more specific embodiment is shown in FIG. 6. In this scenario, an enduser 600 has been associated with an edge server machine 602 via overlaynetwork DNS in the usual manner. An “end user” is a web browser useragent executing on a client machine (e.g., desktop, laptop, mobiledevice, tablet computer, or the like) or mobile application (app)executing on such a device. An “end user” communicates with the edgeserver machine via HTTP or HTTPS, and such communications may traverseother networks, systems, and devices. Edge server machine executes ametadata-configurable web proxy process (GHost) 604 managed by theoverlay network provider, and an associated stream-based datadeduplication process 606. As will be described, the dedupe processtheoretically performs data compression on all blocks from all filesfrom all CDN customers. In this approach, pieces of a file from adifferent URI may be used to perform deduplication, as well as piecesfrom multiple files at the same time. The edge server machine 602 may bea “child” to one or more “parent” nodes, such as a parent GHost process608 executing on another overlay server appliance (not shown). In thisexample, GHost process 608 is a “pass-through” and does not providedifferencing functionality; it may be omitted.

As also seen in FIG. 6, requests from the client side are directed to an“origin” server 612. The origin (or target) server 612 is a server thattypically executes in an overlay network customer infrastructure (orperhaps some other hosted environment, such as a third party cloud-basedinfrastructure). Typically, origin server 612 provides a web-basedfront-end to a web site or web-accessible customer application that isdesired to be accelerated using the overlay network infrastructure. Inthis example scenario, which is not intended to be limiting, the originserver 612 executes in the customer's own private network 614. Customerprivate network 614 includes a physical machine 615. That machine (orsome other machine in the customer network) may support another webproxy process 618, and an associated dedupe process 620. Web proxy 618need not be metadata-configurable, nor does it need to be managedactively by the overlay network. The architecture shown above is notintended to be limiting, but rather is provided as just an example.

The following is a description of an end-to-end flow. In this scenario,and as noted above, “GHost” refers to a metadata-configurable web proxyprocess executing on an edge appliance in an overlay network, “ATS”refers to an overlay network web proxy process executing on an appliancewithin a customer network or infrastructure but distinct from theoverlay network, and the de-dupe process can perform de-duplication withrespect to all blocks from all files local to the specific customer'snetwork (in this example embodiment). As noted above, and depending onthe network architecture employed, a library may also be shared so thatthe associated de-dupe process can perform de-duplication with respectto all blocks from all (or some number of the) overlay networkcustomers. In the illustrated embodiment, a GHost (or ATS) process asthe case may be communicates with an associated dedupe process via aninterface (e.g., localhost).

In a representative (but non-limiting) implementation as shown in FIG.6, the overlay network provider provides software that runs within acustomer's infrastructure (the private network), e.g., as a virtualmachine (VM) or “edge appliance.” The edge appliance 610 preferably islocated either in the DMZ or behind an enterprise firewall and it mayexecute on a hypervisor (e.g., VMware ESXi (v. 4.0+)) 616 supported andmanaged by the overlay network customer. In one preferred embodiment,the edge appliance is distributed as a 64-bit virtual appliancedownloaded via an overlay network customer portal (extranet). Each edgeappliance requires at least one publicly-routable IP address and may beconfigured by the overlay network, preferably over a secure connection.

Thus, according to the above approach, at least one server associatedwith a tenant origin is equipped (or associated) with a dedupe engine.When a request comes for content from an edge server, the request isrouted through a dedupe cache parent for the origin. The cache parentretrieves the content (perhaps from origin) and then, depending on thecontent size and any applicable configuration parameters, performsdeduplication. If deduplication occurs, the parent cache examines itsdictionary; if it can compress the object (by replacing chunks of bytesthat it has already seen with the names that have already been assignedfor those chunks), it does so. The cache parent then sends thecompressed object to the edge server. Separately, the dedupe cacheparent processes the object to store newly-seen chunks of bytes,entering them into the library that it maintains. When the compressedobject is received at the edge server, as described above, the edgeserver processes the compressed object by looking for chunks that werereplaced by names and then retrieving the original chunks using thenames, as has been described.

Generalizing, according to this disclosure, as a stream goesthrough/traverses a parent node, the parent node breaks the stream intochunks. For every chunk, the parent then makes what is, in effect, a“guess” regarding whether the child node to which the stream is beingsent has that chunk. The “guess” may be informed in any way, e.g., itmay be statistical, probabilistic, based on some heuristic, be derivedbased on executing an algorithm, be based on the relative location ofthe child, be based on load, latency, packet loss, or other data, or bedetermined in some other manner. If the parent's belief is that thechild does not have the chunk already, it sends the actual data. If,however, the parent's belief is that the child likely has the chunk,then the parent just sends the name/fingerprint. As the child gets theencoded stream and begins to decode the stream, for every chunkreference/name, the child then looks up the name in its own locallibrary/dictionary. If the chunk is there, the child re-expands it. If,however, the chunk is not present, the child performs an on-demandrequest (e.g., to the encoding peer/region) requesting the actual datafor the chunk.

With this approach, all the known benefits of a CDN (e.g., loadbalancing, caching, WAN acceleration, and so forth) are leveraged.Importantly, the edge server does not need to maintain a symmetriclibrary for the origin. Of course, the edge server might well have thechunks in cache but, if it does not, it follows the usual CDN-likeprocedure to retrieve them (e.g., through a cache hierarchy or thelike), ultimately retrieving them from the dedupe cache parent ifnecessary.

The GHost process has the capability of determining whether a request isto be handled by the deduplication process. One technique for makingthis determination uses tenant-specific metadata and the techniquedescribed in U.S. Pat. No. 7,240,100.

The dedupe module may run as a buddy process or an in-process librarywith respect to GHost. The communication mechanism between GHost and themodule may be over shared memory, localhost, TCP, UDS, or the like. Inan alternative embodiment, the client-side dedupe module itself may beplaced directly on a client device, such as an end user client (EUC)network machine, a mobile device handset, or the like.

Preferably, whether dedupe is turned on may be controlled by metadataconfigurations, preferably on a per-tenant basis.

As noted above, preferably the dedupe mechanism is not invoked for filesthat are too small. Small object aversion support thus provides a way tointelligently avoid performing otherwise risky deduplication operationsthat might incur an extra RTT on a cache miss. In one approach, this maybe accomplished by having GHost bypass the dedupe operation for POSTsand responses that include a “Content-Length” header under a certainthreshold. Most dynamic content, however, uses chunked transferencoding, which means that the size of the object is not known inadvance. Thus, absent some determination to avoid deduplication based onother criteria, GHost should pass the request through the mechanismdescribed.

In addition, preferably the fingerprint is only sent when there is goodassurance that the other side may have the data. Thus, preferably thefingerprint is only sent if the block was seen in the same or a priorstream.

Some file formats (like Huffman encoding) are heavily compressed as wellas jumbled. Commercial deduplication systems often offer systems withintheir deduplication engines to decode those file types into morededuplication-friendly formats prior to performing fingerprinting andchunking. Such approaches may be implemented herein as well. Inparticular, each side (whether in GHost or in the dedupe module itself)may implement per file format decompression filters to better ensurecached block hits.

The GHost/dedupe module solution described herein may also interoperatewith protocol terminators. Protocol terminators are pieces of softwarethat terminate a protocol (such as CIFS or MAPI) and convert it, e.g.,to http or http(s).

The dedupe module may interoperate with other CDN mechanisms, such asFEO techniques.

As shown in FIG. 6, 1 dedupe module as described herein may be locatedwithin an enterprise network, such as in a machine associated with theoverlay network that is located in an enterprise DMZ.

As also shown in FIG. 6, a dedupe module as described herein may belocated within a virtual machine (VM) associated with an enterprise thatuses or interoperates with the overlay network. This architecture is nota limitation, however, as the forward proxy need not be positionedwithin an enterprise (or other customer private network).

The dedupe techniques described herein may be used in association withone or more other CDN service offerings, to facilitate CDN node-to-nodecommunications (in-network deduplication), or the like.

The GHost and dedupe modules are implemented in software, executed inone or more processors, as a specialized machine.

There is no limitation on the type of data that may be processed by thedescribed technique. Indeed, for certain data types (such as PII), datadeduplication such as described herein has significant advantages overcaching alone.

The dedupe function may be implemented in a daemon process, namely, as aset of computer program instructions executed by a hardware processor.The daemon may function as both the client and the server in theHTTP-based protocol described above. Preferably, it is shunted into oronto the servers (e.g., GHost) at the ends of a high latency leg ofcommunication within an overlay network. As described above, preferablymetadata configuration data determines whether a particular request (onthe sending side of the connection) should be considered a request thatshould be accelerated using the protocol.

In general, the approach described herein enables the overlay servers toremove redundant data it is sending between peers on the network,instead sending much smaller fingerprints. This reduces the overall sizeof the data on the wire drastically for transactions that have highamounts of duplicate data, thus reducing the amount of time for deliveryto the end user. In addition, the reduced data results in loweredoperating costs on the network as the amount of information transferredand the bandwidth requires decreases.

The above-described approach is highly scalable, and it works for anytype of content, and over any type of network. The client is aconventional desktop, laptop or other Internet-accessible machinerunning a web browser or other rendering engine (such as a mobile app).The client may also be a mobile device. As used herein, a mobile deviceis any wireless client device, e.g., a cellphone, pager, a personaldigital assistant (PDA, e.g., with GPRS NIC), a mobile computer with asmartphone client, or the like. Other mobile devices in which thetechnique may be practiced include any access protocol-enabled device(e.g., iOS™-based device, an Android™-based device, or the like) that iscapable of sending and receiving data in a wireless manner using awireless protocol. Typical wireless protocols are: WiFi, GSM/GPRS, CDMAor WiMax. These protocols implement the ISO/OSI Physical and Data Linklayers (Layers 1 & 2) upon which a traditional networking stack isbuilt, complete with IP, TCP, SSL/TLS and HTTP. In a representativeembodiment, the mobile device is a cellular telephone that operates overGPRS (General Packet Radio Service), which is a data technology for GSMnetworks. A mobile device as used herein may be a 3G- (or nextgeneration) compliant device that includes a subscriber identity module(SIM), which is a smart card that carries subscriber-specificinformation, mobile equipment (e.g., radio and associated signalprocessing devices), a man-machine interface (MMI), and one or moreinterfaces to external devices (e.g., computers, PDAs, and the like).The techniques disclosed herein are not limited for use with a mobiledevice that uses a particular access protocol. The mobile devicetypically also has support for wireless local area network (WLAN)technologies, such as Wi-Fi. WLAN is based on IEEE 802.11 standards.

Directed Cyclic Graphs

Fingerprinting (using SHA-1 for example) provides hashes that are 20bytes in length, and, in one implementation of the above-describedtechnique, typically replaces blocks in the data stream that have anaverage size of 128 bytes, thus creating a maximum theoreticalcompression limit of 20/128=15%. To increase that percentage, anadditional compression mechanism preferably is used. This mechanismprovides wire compression, and it is referred to as the Directed CyclicGraph method (DCG). It is now described.

As used herein, a directed cyclic graph (DCG) represents temporal andordered relationships between (and among) chunks of data that have beenseen in streams passing between peers (that execute dedupe engines inthe manner described above). Each node (e.g., a circle) in a DCGrepresents a chunk of data. Its label preferably denotes a fingerprint(in practice fingerprints are much larger, but this shorter notation isfor descriptive purposes). Each edge (e.g., an arrow) in a DCGrepresents a transition that the machine has seen. Now, assume that thefirst time a deduplication system such as described above in FIG. 6loads and sees a stream of data; the resultant fingerprints are:[A][B][C][D][E][F][G]. This nomenclature means that the machine has seenchunk [A] followed by [B] followed by [C], and so on for chunks[D][E][F][G]. An initial directed cyclic graph of these fingerprintswould then appear as shown in FIG. 7.

By convention, nodes A through F are Intermediate Nodes. An IntermediateNode then is any node with degree “out” (outward) of exactly one (1).Node G is a Terminal Node. A Terminal Node is a node that has degree outof exactly zero.

Now, assume another stream of data comes in to the peer node and that isprocessed with the following fingerprints: [B][C][D][E][X][Y]. Thisoperation would internally modify the DCG of FIG. 7 to look like FIG. 8.In this example, a new type of node has been introduced and is referredto as an Overflow Node. An Overflow Node is a node with degree outgreater than one. In FIG. 8, this is node E.

According to the DCG scheme of this disclosure, a node in a DCG has aset of state transitions. Preferably, the allowed state transitions fora node in the compression DCG scheme are then as follows. Nodes beginlife in a Terminal Node state, and nothing follows them. Once anothernode follows the node in question, its state transitions toIntermediate, and it may never go back to the Terminal state again (asits degree out has forever been changed). If any other nodes (other thanthe one already mentioned) ever immediately follow the node in question,its state transitions to Overflow, and again the state may nottransition back to Intermediate or Terminal (as its degree out has beenforever altered).

Once the directed cycle graph is in place on both peers, a variant ofrun length encoding is then carried out, as will now be described.Assume another stream of data is seen that looks like the following:[A][B][C][D][E][X]. When sending the fingerprints to the decoding peer,the encoder may then state as follows: start at node A (FIG. 8) and “godown four steps.” (There is no ambiguity in this if the DCGs on eachpeer are in sync). Because each node has degree out of exactly one, itis clear what nodes to which this instruction refers. Then, at node E, adecision must be made because this is an Overflow Node. In other words,the encoder must direct the decoding peer which branch to traverse. Itdoes this by simply sending a new record for X.

According to this scheme, these stretches of nodes with degree out ofone that are connected together are called Strands. When communicatingwith a peer, the sending peer sends a Strand Record that represents thewire data. It is possible that a DCG on one peer could fall out of syncwith the graph on another peer. In that case, it is possible that theencoding peer would instruct the decoding peer to start at a particularnode and go down a certain number of steps, and that the decoding peeris capable of doing this but the data is different. According to anaspect of the DCG scheme, this is guarded against by providing a hash ofthe fingerprints that are to be traversed. Therefore, a Strand Recordpreferably is composed of the following tuple:

[Starting Fingerprint][Number of Nodes][Hash of Nodes Below StartingFingerprint]

If the decoding peer cannot verify the Strand Record's signature, thenpreferably the decoding peer sends a Missing Strand Request to theencoding peer, as described in more detail below.

Returning back to the DCG terminology, the purpose of the “cyclic” partof the graph can be seen by way of an example. Often, there may becircumstances where a strand loops back in on itself. For example, usingthe above examples, a peer might see a stream that looks like thefollowing: [A][B][C][D][A][B][C][D][A][B][C][D][A][B][C][D][E][X][Y][G].This would generate a DCG such as shown in FIG. 9. Then, if at a latertime if the following data stream were sent:[A][B][C][D])×100[E][X][Y][G], the following would be output:[A:3:HASH(B·C·D)][A:3:H(B·C·D)] . . . [E:3:HASH(X·Y·G)], where the[A:3:HASH(B·C·D)] sequence appears 100 times. To avoid this repetitionproblem, and according to this disclosure, the output of the DCG may bepassed through a deflation algorithm. An algorithm that usesLempel-Ziv-77 (or equivalent) to remove repetition in the stream may beused for this purpose. In addition, a coding, such as Huffman Coding,may also be used to minimize the size of the output tokens. Thisapproach can compress the 100 A Strand Records (in this examplescenario) into a single token sequence.

The DCG approach as described above facilitates significant on-the-wirecompression. Indeed, many file formats have large strings of data infile headers that simply do not change. In addition, many file types(e.g. Microsoft PowerPoint files, Microsoft Word files, and the like)routinely have stretches of thousands of fingerprints with degree out ofone. This is intuitively correct, as low entropy files generally do notchange much from one version to the next. The stretches that do notchange are represented by long strands of nodes with degree out of one.This content is then processed into Strand Records that, in turn, may beprocessed as described above such that the information on-the-wire isgreatly reduced. In practice, the DCG method compresses significantlytighter than GZIP and other known techniques.

In summary, by instantiating and maintaining directed cyclic graphs ateach side of the communication, on-the-wire data compression isfacilitated. In particular, DCGs provide a way to compress data basedupon temporal locality (at a respective peer) of ordered chunks withinsimilar prior-seen data.

Cache Synchronization Using Missing Strand Requests

As noted above in the discussion regarding FIG. 6, preferably thededuplication system uses a cache synchronization protocol that involvespeers communicating with each other explicitly, e.g., by a peer makingcertain assumptions about what another peer might have, or otherwise. Nomatter what cache synchronization protocol exists, the system shouldaccount for the fact that something could occur to cause a mismatch incaches between peers. If this occurs, it must be possible to resolve themismatch and make forward progress. Thus, according to a further featureof this disclosure, the notion of Missing Strand Requests addresses thisproblem. In particular, whenever a strand is not available for decode onthe child, the decoding peer (the child) can make a request back up tothe encoding peer (or region of peers) and request the raw data for thenoted strand. The processing of data on the decoder side is very fastand thus a missing strand should be detected and a request sent back tothe encoder within only a small processing overhead time. This approachensures that, irrespective of what cache synchronization protocol isbeing utilized, there is a fallback mechanism to ensure that atransaction can complete. The missing strand support thus handles thepossibility of complete cache misses, and it can be used in conjunctionwith the cache synchronization approach described above (namely,assuming that the decoding peer has a given block of data if the localencoding peer already has it, and assume the decoding peer does not ifthe local encoding peer does not).

A Missing Strand Request is a mechanism by which a downstream peer canrequest (from an upstream peer) a particular section of a DCG along withits associated raw data so that the downstream peer has sufficient datato enable it to reproduce and store the graph and blocks on its side. Itprovides a cache synchronization method that, together with the use ofdirected cyclic graphs, results in significant performance enhancements.

Whether Strand Records are sent down the wire to the decoding peer (inlieu of the raw data itself) may be implementation-, orcontext-dependent. When the Missing Strand support (as described above)is in place, there may be an assumption that the decoding peer has agiven block of data if the local encoding peer already has it, and thatthe decoding peer does not if the local encoding peer does not; theseassumptions may be appropriate in certain circumstances as, if there isa cache miss, the missing strand support is activated. The conclusionthat Strand Records thus should always be used, however, need notnecessarily follow. The more two peers communicate with each other, themore often the Strand approach works as items seen first by one are alsoseen first by the other. When the longevity of peer communication ingeneral is short, however, relying on the above assumptions can lead toa parent believing a child has content just because the parent has itlocally. In a scenario where a parent for a hot piece of data talks to afirst edge region and synchronizes appropriately, every other edgeregion that the parent talks to after this will incorrectly be assumedto have the data. Accordingly, the use of Strands will be mostappropriate for hot content, as for any given child decode region, thatregion will only suffer a stall for the first user that needs todownload the missing strand. While this user will suffer an additionalRTT to fetch the strand, deduplication will still have saved sufficienttime on the download (such that the additional RTT might not benoticed). All subsequent users, however, will then benefit from the hotcache.

As a variant, other heuristics may be factored into the decision of whento send just a Strand as opposed to the backing data. For example, ifthe parent encoding peer has a strand but has not talked to a peerregion that is in-line to receive the stream for a given configurabletime, the parent can gauge the risk of sending just the strand recordbased on the RTT. If it is determined that there may be too great apenalty on a cache miss, the raw data may then be sent in lieu of thestrand.

Cache synchronization using Missing Strand Request processing asdescribed herein provides a robust and reliable mechanism to keep pairsof disparate dictionaries synchronized on demand and when needed duringthe deduplication process (i.e., while traffic is flowing through(transiting) the dedupe peers).

The use of directed cyclic graphs and missing strand requests asdescribed herein finds particular utility in providing on-the-wirecompression between an edge server and a parent in the context of anoverlay network. That particular use scenario is not intended to belimiting, however, as the techniques herein may be used between any twocomputing entities including, without limitation, client and edgeserver, forward server and origin, and the like.

Summarizing, the deduplication approach described herein enables removalof redundant data being sent between peers on the network, insteadsending much smaller fingerprints. This reduces the overall size of thedata on the wire drastically for transactions that have high amounts ofduplicate data, thus reducing the amount of time for delivery to the enduser. In addition, the reduced data results in lowered operating costson the network as the amount of information transferred and thebandwidth requires decreases.

A deduplication system as described herein is capable of removingredundant data patterns between peers in order to provide significantcompression savings. The architecture approach shown in FIG. 6 may beused, but this is not a requirement, as the dedupe functionality may beimplemented in any manner depending on the associated peerimplementation. More generally, the dedupe functionality is implementedas co-processes on peer nodes. As noted, for a given request, a dedupeprocess near an origin replaces well-defined sections of the actualresponse data with references to it, while the dedupe process near therequester reverses the process, restoring the actual data for thereferences found. In this way, the amount of common data repeatedlytransmitted between the nodes is reduced.

As used herein, a “fingerprint” is a binary compressed representation ofa string of data, such as a file. Typically, a fingerprint is a hashwith good cryptographic properties, such as SHA-1.

More generally, the techniques described herein are provided using a setof one or more computing-related entities (systems, machines, processes,programs, libraries, functions, or the like) that together facilitate orprovide the described functionality described above. In a typicalimplementation, a representative machine on which the software executescomprises commodity hardware, an operating system, an applicationruntime environment, and a set of applications or processes andassociated data, that provide the functionality of a given system orsubsystem. As described, the functionality may be implemented in astandalone machine, or across a distributed set of machines. Thefunctionality may be provided as a service, e.g., as a SaaS solution.

While the above describes a particular order of operations performed bycertain embodiments of the invention, it should be understood that suchorder is exemplary, as alternative embodiments may perform theoperations in a different order, combine certain operations, overlapcertain operations, or the like. References in the specification to agiven embodiment indicate that the embodiment described may include aparticular feature, structure, or characteristic, but every embodimentmay not necessarily include the particular feature, structure, orcharacteristic.

While the disclosed subject matter has been described in the context ofa method or process, the subject disclosure also relates to apparatusfor performing the operations herein. This apparatus may be speciallyconstructed for the required purposes, or it may comprise ageneral-purpose computer selectively activated or reconfigured by acomputer program stored in the computer. Such a computer program may bestored in a computer readable storage medium, such as, but is notlimited to, any type of disk including an optical disk, a CD-ROM, and amagnetic-optical disk, a read-only memory (ROM), a random access memory(RAM), a magnetic or optical card, or any type of media suitable forstoring electronic instructions, and each coupled to a computer systembus.

While given components of the system have been described separately, oneof ordinary skill will appreciate that some of the functions may becombined or shared in given instructions, program sequences, codeportions, and the like.

Preferably, the functionality is implemented in an application layersolution, although this is not a limitation, as portions of theidentified functions may be built into an operating system or the like.

The functionality may be implemented with other application layerprotocols besides HTTPS, such as SSL VPN, or any other protocol havingsimilar operating characteristics.

There is no limitation on the type of computing entity that mayimplement the client-side or server-side of the connection. Anycomputing entity (system, machine, device, program, process, utility, orthe like) may act as the client or the server.

What is claimed is as follows:
 1. A data deduplication system, thesystem comprising: a sending peer entity maintaining a first datadictionary, and a receiving peer entity maintaining a second datadictionary; the sending and receiving peer entities comprisingprocesses, wherein each entity comprises stream-based data deduplicationsoftware executed by a hardware processor that is configured to examinedata that flows through the entity and to replace blocks of the datawith references that point into the entity's associated data dictionary;the sending peer entity further including: a directed cyclic graphrepresenting temporal and ordered relationships among blocks of datathat have been seen in the data stream by the sending peer entity, thedirected cyclic graph comprising one or more nodes, wherein a noderepresents a block of data and has associated therewith a label denotinga fingerprint associated with the block of data; and an encoder thatuses information in the directed cyclic graph to replace one or morereferences to blocks of data that have been seen in the data stream bythe sending peer entity by a compact data representation.